Abstract
Analysing manual work is an important task in industrial companies with high labour costs and labour intensive work processes. Industrial Engineer s can use the results of these analyses to identify potentials and improve productivity to maintain and improve competitiveness. To obtain goal-oriented results the processes need to be analysed in detail. One method that yields detailed information is the MTM-1-method. However, it requires a lot of effort and special knowledge. This presents a big hurdle, especially for companies with small production quantity. One option to reduce the effort and the required knowledge is using motion capture technology. This technology is capable to record human motions and to translate them into data that can be processed digitally. Known representatives are 3D cameras and motion capture suits. They track positions and postures of the human body, thus allowing conclusions about human movements. This paper presents an approach to detect body motions in accordance to MTM-1 using motion capture data from 3D cameras. The detected motions are then analysed with respect to productivity to show improvement potential.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Sumanth, D.J.: Productivity Engineering and Management: Productivity Measurement, Evaluation, Planning, and Improvement in Manufacturing and Service Organizations. McGraw-Hill, New York (1984)
Weber, H.K.: Rentabilität, Produktivität und Liquidität. Größen zur Beurteilung und Steuerung von Unternehmen. Gabler, Wiesbaden (1998)
Bokranz, R., Landau, K.: Produktivitätsmanagement von Arbeitssystemen: MTM-Handbuch. Schäffer-Poeschel, Stuttgart (2006)
MTM-1. Lehrgangsunterlage; A/AB. Deutsche MTM-Vereinigung e.V, Hamburg (2014)
Benter, M.: Analyse von Arbeitsabläufen mit 3D-Kameras. Dissertation. TUHH, Institut für Produktionsmanagement und -technik, Hamburg (2018)
Womack, J.P., Jones, D.T.: Lean thinking. Ballast abwerfen, Unternehmensgewinne steigern. Campus, Frankfurt am Main (2004)
Liker, J.K.: The Toyota Way: 14 Management Principles from the World’s Greatest Manufacturer. McGraw-Hill, New York (2004)
Jackèl, D., Nenreither, S., Wagner, F.: Methoden der Computeranimation. Springer, Berlin (2006)
Kitagawa, M., Windsor, B.: MoCap for Artists: Workflow and Techniques for Motion Capture. Elsevier/Focal Press, Amsterdam (2008)
Steward, J., et al.: Performance assessment and calibration of the Kinect 2.0 time-of-flight range camera for use in motion capture applications. In: Conference Papers of FIG Working Week, Sofia, Bulgarien, pp. 1–14 (2015)
Zhang, Z.: Microsoft Kinect sensor and its effect. IEEE Multimed. 19, 4–10 (2012)
Benter, M., et al.: Automatisierung von Ergonomiebewertungen durch Bewegungserfassung am Beispiel des Ergonomic Assessment Worksheet (EAWS). In: Gesellschaft für Arbeitswissenschaft e.V.: Gestaltung der Arbeitswelt der Zukunft, Dortmund (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Benter, M., Kuhlang, P. (2020). Analysing Body Motions Using Motion Capture Data. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2019. Advances in Intelligent Systems and Computing, vol 959. Springer, Cham. https://doi.org/10.1007/978-3-030-20040-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-20040-4_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-20039-8
Online ISBN: 978-3-030-20040-4
eBook Packages: EngineeringEngineering (R0)